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Cited by in F6Publishing
For: An C, Jiang Y, Huang Z, Gu Y, Zhang T, Ma L, Huang J. Assessment of Ablative Margin After Microwave Ablation for Hepatocellular Carcinoma Using Deep Learning-Based Deformable Image Registration. Front Oncol. 2020;10:573316. [PMID: 33102233 DOI: 10.3389/fonc.2020.573316] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
Number Citing Articles
1 Christou CD, Tsoulfas G. Role of three-dimensional printing and artificial intelligence in the management of hepatocellular carcinoma: Challenges and opportunities. World J Gastrointest Oncol 2022; 14(4): 765-793 [DOI: 10.4251/wjgo.v14.i4.765] [Reference Citation Analysis]
2 Minier C, Hermida M, Allimant C, Escal L, Pierredon-Foulongne MA, Belgour A, Piron L, Taourel P, Cassinotto C, Guiu B. Software-based assessment of tumor margins after percutaneous thermal ablation of liver tumors: A systematic review. Diagn Interv Imaging 2022:S2211-5684(22)00033-X. [PMID: 35246412 DOI: 10.1016/j.diii.2022.02.004] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Ahn JC, Qureshi TA, Singal AG, Li D, Yang JD. Deep learning in hepatocellular carcinoma: Current status and future perspectives. World J Hepatol 2021; 13(12): 2039-2051 [DOI: 10.4254/wjh.v13.i12.2039] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]